Nokia today announced its participation in a new industrial consortium led by the Finnish Border Guard to develop next-generation counter-drone capabilities for patrol vehicles and boats. Nokia’s Defense unit will provide an intelligent network solution that enables secure, high-performance connectivity, real-time data exchange and interoperability across systems. This initiative aims to support border security duties, surveillance, protection of territorial integrity and the safeguarding of critical infrastructure nationwide.

The Finnish Border Guard initiative focuses on building a sovereign, integrated counter-unmanned aerial systems (UAS) and threat detection capability. By connecting platforms, sensors and command-and-control systems, the solution is designed to deliver enhanced real-time situational awareness and enable faster, more coordinated responses to evolving multi-domain threats across land and sea.

Nokia’s role highlights the growing importance of trusted and intelligent connectivity as a foundation for modern defense and border security. As drones become more accessible and widely used, threat detection, sensing and connectivity must work seamlessly to protect personnel, infrastructure and mission effectiveness. Through the consortium, Nokia Defense will work with key partners to support a scalable, future-ready system aligned with national and allied requirements.

"Reliable, secure connectivity is becoming essential to how defense organizations detect, understand and respond to fast-moving threats. By contributing Nokia’s intelligent connectivity and sensing technology to this consortium, we are helping build an operational and interoperable solution that gives border authorities the real-time awareness and resilience they need in complex land and maritime environments," said Mikko Hautala, Chief Geopolitical & Government Relations Officer, and Chairman, Nokia Defense.

The project includes the procurement and deployment of evaluation platforms, connectivity and sensing capabilities, and system integration. The solutions will be evaluated during 2027 and early 2028.

Nokia and Databricks have successfully completed a joint proof of concept (PoC) demonstrating a unified, substrate-agnostic data platform designed to support AI-driven autonomous networks. The collaboration, announced on 24 June 2026, shows how telecommunication providers can simplify fragmented data environments and deploy real-time analytics at scale, enabling faster decision-making, improved network performance, and more efficient operations. The PoC addresses the industry challenge of siloed operational and business support systems by validating a common data platform that runs seamlessly across different cloud environments or on-premise infrastructure.

Technical validation and architecture

The PoC confirmed the ability of Databricks and Nokia to develop a joint architecture that efficiently handles the massive scale and real-time ingestion speeds required to feed network data to AI agents for automated, cross-domain decision-making. Engineering teams focused on a real-time performance management use case, simulating analytics ingestion with an intent to scale quickly to match tier-1 operator scale in the cloud.

Key technical breakthroughs

The collaboration delivered several technical advancements designed to simplify how telecom operators build and run data-driven services across different environments:

Data fabric capabilities

The project highlighted a data fabric built for the agentic world, featuring query-time data products that compute derived metrics on read rather than duplicating data. It also validated zero-copy sharing for lightweight, real-time cross-domain data consumption and a mechanism to selectively feed upper temporal layers in the cloud for retrospective tasks like root-cause analysis.

Strategic outlook

Nokia and Databricks plan to continue their collaboration around enhancing autonomous network capabilities. The goal is to help operators transition to a future where AI applications increasingly access, correlate, and act on large-scale network data in real time.